When Medical Providers Identify Potentially Lost to Care, HIV-Positive Individuals: A Comparison of Lost-to-Care and In-Care Populations

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Authors of the Poster Presentation Goes Here
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Background
• Identifying and linking HIV-infected persons to medical care
is a key component of the National HIV/AIDS Strategy.1
• Care status is dynamic, and patients often enter and exit
care repeatedly over time.
• An estimated 49% of the almost 23,000 people living with
HIV (PLWH) in 2012 within Houston/Harris County were
lost to HIV care 2.
• Partnerships between medical providers and health
departments (HD) provide HD with a list of prioritized,
potentially lost-to-care provider patients. HD can help
providers distinguish truly lost-to-care persons from those
currently in care due to:
1. patient movement to different providers
2. patients returned to care without public health
intervention
• Houston/Harris county is a wide spread urban area over
1700 sq. miles, and it has a limited public transportation
system 3.
Methods
• Potentially lost-to-care patients were referred to the
Houston Department of Health and Human Services
(HDHHS) by 3 local Ryan White (RW)-funded HIV medical
providers for possible re-linkage intervention (N=271) from
June 2013 to December 2014.
• Criteria for referrals were that they needed to be in care at
one time and the provider had no evidence of care for the
patients for at least 6 months.
• The HDHHS investigated the referrals for evidence of care
within the 6 months prior (HIV medical care visit or CD4/VL
laboratory test result), residence in Houston/Harris County,
deceased, and incarceration status.
• Referrals deemed out-of-care after record searches across
multiple data systems were referred to service linkage (SL)
services. SL is non-medical case management
specializing in re-linking patients to HIV care.
ANALYSES
• 138 referrals qualified for SL services (out-of-care), and
133 did not qualify due to evidence of current care.
• Simple logistic regression and multivariable logistic
regression compared socio-demographic characteristics
between in-care and out-of-care referrals using SAS 9.3.
• ArcGIS 10.3 generated the proximity measure using Point
Distance of the proximity toolset. The point-to-point
measure was most current residential address of referrals
to the nearest RW-funded HIV provider clinic.
• ArcGIS 10.3 generated a density layer of all provider
referrals using Kernel Density.
This study was supported by cooperative agreements from the Merck Foundation and the Centers for Disease Control and Prevention (CDC). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the sponsoring organizations. Special thanks to Texas Department of State Health Services, the Houston Area Ryan White Planning Council, and the Houston HIV Prevention Community Planning Group. Further gratitude for the Ryan White
Grant Administration of Harris County Department of Health and Environmental Services and to the following Ryan White Care providers: Harris Health System, Houston Area Community Services, and St. Hope Foundation. This presentation was made possible with support from the Baylor-UTHouston Center for AIDS Research (CFAR), an NIH-funded program (AI036211). The authors appreciate the contributions of all research and support staff at the affiliated institutions.
Table 1. Multivariable Logistic Regression Results Results
• Sex, race, ethnicity, age and duration of HIV positivity were
not significantly different between those who were in care
and those who were lost to care (Table 1).
• Direct proximity from the most recent residence in miles, as
a continuous or categorical variable, to the nearest HIV
provider clinic was not significantly different between those
in care and those who were lost to care (Table 1).
• There are areas with a high density of potentially out-of-
care HIV patients that do not have a nearby Ryan White
funded provider clinic (Fig. 2).
Conclusions
• Intervention strategies should be aimed at common barriers
to care and not particular groups characteristics.
• Direct residential proximity to provider clinics may not play
a role in returning to care, but physical barriers or bus
routes may influence care status, particularly in the
widespread metropolitan area of Houston/Harris County.
• Between 2000 and 2010, the rate of new HIV diagnosis
was positively associated with increasing percentage below
poverty in Houston, TX 4.
• HIV/AIDS continues to disproportionately affect
impoverished people and others who are underserved by
healthcare and prevention systems. A strategy for
increasing access to care is emphasizing ancillary services
such as transportation assistance.
LIMITATIONS
1.Ecological Fallacy – analyses at the aggregate level
should not be applied to individuals
2.Most recent residential address may not have been the
address when patient sought care in previous 6 months
3.Provider referred, potential lost-to-care individuals may
have never been out of care.
4.Race/ethnicities might not be mutually exclusive
5.Data system records may not be recently updated.
Future analyses should look at proximity measures along
roads or bus routes to better reflect the transportation
environment as a potential barrier to accessing HIV care.
References
1. White House Office of National AIDS Policy. National HIV/AIDS Strategy for the United States. Washington, DC:
The White House; July13, 2010. Available at: http://www.whitehouse.gov/sites/default/files/ uploads/NHAS.pdf2.
Accessed 14 May 2015.
2. Houston Area Ryan White Planning. “OVERALL EMA: Number and Percentage of People with HIV in Selected
Stages of the Continuum of HIV Care , 2012 (Version 2, as of 12-17-13) ” Available at
http://www.rwpchouston.org/Publications/2012_Comp_Plan/Treatment_Cascade.htm. Accessed 14 May 2015.
3. Harris County, TX. United States Census Bureau: State and County Quick Facts. Available at
http://quickfacts.census.gov/qfd/states/48/48201.html. Accessed 2 May 2015.
4. Pilot Project to Analyze Public Health Data for Health Disparities by Socioeconomic Status Using Census Tract
Poverty Level (2013). Houston.
When Medical Providers Identify Potentially Lost to Care, HIV-Positive
Individuals: A Comparison of Lost-to-Care and In-Care Populations
Saroochi Agarwal MS, MSPH1 , Kellie L. Watkins MS1, Camden J. Hallmark MPH1, Raven Bradley MPH1, Richard M. Grimes PhD3, Biru Yang PhD2, Marcia Wolverton MPH2, Marlene McNeese1
1 Houston Department of Health and Human Services, Bureau of HIV/STD and Viral Hepatitis Prevention; 2 Houston Department of Health and Human Services, Bureau of Epidemiology; 3 The University of Texas Health Science
Center, Division of General Internal Medicine
Figure 1. Residential Proximity of Provider
Referrals to Provider Clinics
Figure 2. Kernel Density of Provider Referrals
Presented at the International Association of Providers of AIDS Care Conference ●June 28-30, 2015 ● Miami, FL